First, load in the plotly and data.table libraries and load in the mtcars dataset.
suppressPackageStartupMessages(library(plotly))
suppressPackageStartupMessages(library(data.table))
suppressPackageStartupMessages(library(maps))
dt <- data.table(mtcars, keep.rownames = T)
Next, we use the plotly package to make some cool graphics!
plot_ly(data = dt, x = ~disp, y = ~mpg, type = 'scatter', name = ~rn, color = ~qsec, showlegend = F)
plot_ly(data = dt, x = ~disp, y = ~mpg, z = ~qsec, type = 'scatter3d', split = ~cyl, legendgrouptitle = list(text = 'Number of Cylinders'), hovertext = ~rn, hoverinfo = 'x+y+z+text')
And just for fun, we’ll add an map of the USA using votes.repub from the maps package.
avg.repub <- apply(votes.repub, MARGIN = 1, function(x) mean(x, na.rm = T)) %>%
as.data.table(keep.rownames = T)
avg.repub[, states := state.abb]
plot_ly(avg.repub,
z = ~.,
type = 'choropleth',
color = ~.,
locations = ~states,
locationmode = 'USA-states',
colors = 'Reds') %>%
layout(title = 'Average Republican Vote Percentage by State (1856 - 1976)',
geo = list(scope = 'usa',
projection = list(type = 'albers usa')))